Non-Parametric Methods in Psychological Research
Non-Parametric Methods in Psychological Research
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心理学研究中的非参数方法
DOI：
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发表时间：
1959
期刊：
影响因子：
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通讯作者：
J. Gaito
中科院分区：
文献类型：
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作者：
J. Gaito
近年来发展了不依赖已知分布参数进行统计推断的统计技术。这些被称为非参数或无分布方法。心理学家熟悉的关于这一主题的主要陈述可能是爱德华兹(8)、摩西（22）、莫斯塔勒和布什（23）以及西格（27）。然而，在这个领域还有许多其他的论文（例如，14,21,31）。这些技术的发展主要是为了避免像参数技术那样需要做出许多假设，从而提供某些优势。然而，根据最近的研究，似乎至少对于一种参数技术，所引用的非参数分析的一些假定优点是不成熟的，因为这种参数技术的假设并不像曾经设想的那样具有限制性。本文的目的是考虑不符合方差分析技术的假设对随后的显著性检验的影响，并建议在这一领域，非参数技术在心理学研究中的应用非常有限。
In recent years statistical techniques have been developed which do not rely on parameters of a known distribution in making statistical inferences. These have been called non-parametric or distribution-free methods. The main presentations of this subject matter with which psychologists are familiar are probably those by Edwards ( 8 ) , Moses ( 22 ) , Mosteller and Bush ( 2 3 ) , and Siege1 (27). However, there are numerous other treatises in this area (e.g., 14, 21, 31). These techniques have been developed mainly to avoid the need for making numerous assumptions as is the case with parametric techniques, thus providing certain advantages. However, in light of recent research it appears that at least with one parametric technique some of the assumed advantages of non-parametric analyses cited have been premature inasmuch as the assumptions of this parametric technique are not as restrictive as once supposed. The purpose of this paper is to consider effects of failure to meet assumptions of the analysis of variance technique on subsequent tests of significance and to suggest that in this area non-parametric techniques be given very limited use in psychological research.